mcp-server
Server Details
Passport visa, entry & transit requirements for any country pair, with official government sources.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.1/5 across 2 of 2 tools scored.
The two tools have clearly distinct purposes: check_visa performs the main visa check while country_code resolves country names to codes. There is no overlap or ambiguity.
Both tools use underscore-separated lowercase names. While check_visa follows a verb_noun pattern and country_code follows noun_noun, the convention is consistent and clear.
With only two tools, the server is minimal but well-scoped for the narrow domain of visa checking. It covers the essential functionality without being too sparse.
The server covers the core visa check workflow, including a helper to normalize country codes. However, country_code is somewhat redundant since check_visa already accepts country names, but no critical features are missing.
Available Tools
2 toolscheck_visaCheck visa & entry requirementsAInspect
Check whether a traveler holding a given passport needs a visa, and what entry & transit requirements apply, for a destination country — with official government sources. Accepts ISO 3166-1 alpha-2 codes (e.g. "US", "KE") or common country names (e.g. "United States", "Kenya"). Returns a plain-language verdict, the specific requirements by severity, deduped official source links, and a deep link to the full EasyOnward analysis. Read-only and PII-free; the analysis is generic for any citizen of the passport country.
| Name | Required | Description | Default |
|---|---|---|---|
| passport_country | Yes | The traveler's passport-issuing country. ISO 3166-1 alpha-2 code (e.g. "US") or country name (e.g. "United States"). | |
| destination_country | Yes | The destination country. ISO 3166-1 alpha-2 code (e.g. "KE") or country name (e.g. "Kenya"). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the tool is read-only, PII-free, uses official government sources, and returns deduped source links and a deep link. It also clarifies that the analysis is generic. It does not mention rate limits or error handling, but covers key behavioral traits adequately.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured: starts with core purpose, then details input format and output. Every sentence adds value with no redundancy. Suitable length for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description adequately describes the return value (verdict, requirements, sources, deep link). It covers input format and tool behavior. Minor gaps like error handling or caching are not critical, but the description is nearly complete for a read-only query tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter descriptions already provided. The description restates that parameters accept ISO codes or country names, adding minimal value beyond the schema. Baseline score of 3 is appropriate as schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Check whether a traveler holding a given passport needs a visa'. It specifies the verb 'check', the resource 'visa & entry requirements', and the scope (passport country to destination). It distinguishes itself from sibling tool 'country_code' by directly accepting both codes and country names.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (to check visa/entry requirements) and notes it is read-only and PII-free, but does not explicitly state when not to use or mention alternatives like the sibling tool 'country_code'. Score reflects implied usage but lack of explicit guidance on exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
country_codeResolve a country name to its ISO-2 codeAInspect
Resolve a country name (or an existing ISO 3166-1 alpha-2 code) to its uppercase ISO 3166-1 alpha-2 code — e.g. "Kenya" → "KE". Useful before calling check_visa. Returns an error if the name can't be resolved.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | A country name or ISO-2 code, e.g. "Kenya" or "KE". |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the burden. It discloses the uppercase output and error behavior for unresolvable names. However, it lacks details on error type and side effects, which is adequate for a simple lookup tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. The first sentence clearly explains the function with an example, and the second adds usage context and error behavior.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema, no annotations), the description is complete: covers input, output, error handling, and usage scenario.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description adds minimal semantic value beyond the schema. The example in the description mirrors the schema description, earning a baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Resolve' and the resource 'country name to ISO-2 code', with a concrete example. It distinguishes from sibling tool check_visa by noting it is useful before calling that tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Useful before calling check_visa', providing clear context for when to use it. It does not mention exclusions, but the usage is well-defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
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